Class used to store optimum IBayesNet during some inference algorithms. More...

#include <agrum/CN/varMod2BNsMap.h>

Collaboration diagram for gum::credal::VarMod2BNsMap< GUM_SCALAR >:

Public Member Functions
bool	insert (const std::vector< bool > &bn, const std::vector< Size > &key)
	Insert for thread fusion.
bool	insert (const std::vector< Size > &key, const bool isBetter)
	Thread insert.
Constructors / Destructors
	VarMod2BNsMap (const CredalNet< GUM_SCALAR > &cn)
	Thread constructor.
	VarMod2BNsMap ()
	Default constructor that should be used only by InferenceEngine since it has a member variable.
	~VarMod2BNsMap ()
	Destructor.
Getters and setters
void	setCNet (const CredalNet< GUM_SCALAR > &cn)
	Initialize sampleDef from the CredalNet.
void	setCurrentSample (const std::vector< std::vector< std::vector< bool > > > &sample)
	Set the current thread sample and it's hash.
const dBN &	getCurrentSample ()
	Get the current sample as a vector of bits without structure.
const std::vector< std::vector< std::vector< bool > > > &	getSampleDef ()
	Get the sample structure.
const std::vector< dBN * >	getBNOptsFromKey (const std::vector< Size > &key)
	Get optimum IBayesNet (s) without structure of the given variable, modality for min or max.
std::vector< std::vector< std::vector< std::vector< bool > > > >	getFullBNOptsFromKey (const std::vector< Size > &key)
	Get optimum IBayesNet (s) with structure of the given variable, modality for min or max.
Size	getEntrySize () const
	Get the number of IBayesNet stored.

Protected Attributes
hashNet	myHashNet_
	Map id - dBN : get a net from it's id.
varHashs	myVarHashs_
	Map varKey - list(id) : get all optimal nets id from the given key : variable, modality and min=0 ( or max=1 ).
hashVars	myHashVars_
	Map id - list(varKey) : get all variables, modalities associated to this optimal net id.
std::vector< std::vector< std::vector< bool > > >	sampleDef_
	Since all samples have the same structure, this will be used as default initialization (copy constructor) for any sample.
dBN	currentSample_
	The current sampled IBayesNet.
Size	currentHash_
	The current sampled IBayesNet hash.
std::hash< std::vector< bool > >	vectHash_
	The hash fuction.
const CredalNet< GUM_SCALAR > *	cnet
	A pointer to the CredalNet to be used.

Private Types
using	dBN = std::vector< bool >
using	varKey = std::vector< Size >
using	hashNet = gum::HashTable< Size, dBN >
using	varHashs = gum::HashTable< varKey, std::list< Size > >
using	hashVars = gum::HashTable< Size, std::list< varKey > >

Detailed Description

template<typename GUM_SCALAR>
class gum::credal::VarMod2BNsMap< GUM_SCALAR >

Class used to store optimum IBayesNet during some inference algorithms.

Template Parameters

GUM_SCALAR A floating type ( float, double, long double ... ).

Author: Matthieu HOURBRACQ and Pierre-Henri WUILLEMIN(_at_LIP6)

Definition at line 73 of file varMod2BNsMap.h.

Member Typedef Documentation

◆ dBN

template<typename GUM_SCALAR>

using gum::credal::VarMod2BNsMap< GUM_SCALAR >::dBN = std::vector< bool >

private

Definition at line 74 of file varMod2BNsMap.h.

◆ hashNet

template<typename GUM_SCALAR>

using gum::credal::VarMod2BNsMap< GUM_SCALAR >::hashNet = gum::HashTable< Size, dBN >

private

Definition at line 76 of file varMod2BNsMap.h.

◆ hashVars

template<typename GUM_SCALAR>

using gum::credal::VarMod2BNsMap< GUM_SCALAR >::hashVars = gum::HashTable< Size, std::list< varKey > >

private

Definition at line 78 of file varMod2BNsMap.h.

◆ varHashs

template<typename GUM_SCALAR>

using gum::credal::VarMod2BNsMap< GUM_SCALAR >::varHashs = gum::HashTable< varKey, std::list< Size > >

private

Definition at line 77 of file varMod2BNsMap.h.

◆ varKey

template<typename GUM_SCALAR>

using gum::credal::VarMod2BNsMap< GUM_SCALAR >::varKey = std::vector< Size >

private

Definition at line 75 of file varMod2BNsMap.h.

Constructor & Destructor Documentation

◆ VarMod2BNsMap() [1/2]

template<typename GUM_SCALAR>

gum::credal::VarMod2BNsMap< GUM_SCALAR >::VarMod2BNsMap ( const CredalNet< GUM_SCALAR > & cn )

explicit

Thread constructor.

Initialize sampleDef from the CredalNet.

Parameters

cn	The CredalNet to be used.

Definition at line 56 of file varMod2BNsMap_tpl.h.

                                                                                {
      setCNet(cn);
 
      GUM_CONSTRUCTOR(VarMod2BNsMap);
    }

References VarMod2BNsMap(), and setCNet().

Referenced by VarMod2BNsMap(), VarMod2BNsMap(), and ~VarMod2BNsMap().

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◆ VarMod2BNsMap() [2/2]

template<typename GUM_SCALAR>

gum::credal::VarMod2BNsMap< GUM_SCALAR >::VarMod2BNsMap ( )

Default constructor that should be used only by InferenceEngine since it has a member variable.

Definition at line 49 of file varMod2BNsMap_tpl.h.

                                               {
      cnet = nullptr;
 
      GUM_CONSTRUCTOR(VarMod2BNsMap);
    }

References VarMod2BNsMap(), and cnet.

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◆ ~VarMod2BNsMap()

template<typename GUM_SCALAR>

gum::credal::VarMod2BNsMap< GUM_SCALAR >::~VarMod2BNsMap ( )

Destructor.

Definition at line 63 of file varMod2BNsMap_tpl.h.

                                                {
      GUM_DESTRUCTOR(VarMod2BNsMap);
    }

References VarMod2BNsMap().

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Member Function Documentation

◆ getBNOptsFromKey()

template<typename GUM_SCALAR>

const std::vector< std::vector< bool > * > gum::credal::VarMod2BNsMap< GUM_SCALAR >::getBNOptsFromKey ( const std::vector< Size > & key )

Get optimum IBayesNet (s) without structure of the given variable, modality for min or max.

Parameters

key	The constant reference to the variable, modality, min or max.

Returns: The constant vector of not yet constant pointers to the nets.

Definition at line 208 of file varMod2BNsMap_tpl.h.

                                                                                  {
      // return something even if key does not exist
      if (!myVarHashs_.exists(key)) return std::vector< std::vector< bool >* >();
 
      std::list< Size >& netsHash = myVarHashs_[key];   //.at(key);
 
      std::vector< dBN* > nets;
      nets.resize(netsHash.size());
 
      std::list< Size >::iterator it = netsHash.begin();
 
      for (Size i = 0; i < netsHash.size(); i++, ++it) {
        nets[i] = &myHashNet_ /*.at(*/[*it];   //);
      }
 
      return nets;
    }

References myHashNet_, and myVarHashs_.

◆ getCurrentSample()

template<typename GUM_SCALAR>

const std::vector< bool > & gum::credal::VarMod2BNsMap< GUM_SCALAR >::getCurrentSample ( )

Get the current sample as a vector of bits without structure.

Returns: The constant reference to the sampled IBayesNet without structure.

Definition at line 196 of file varMod2BNsMap_tpl.h.

                                                                           {
      return currentSample_;
    }

References currentSample_.

◆ getEntrySize()

template<typename GUM_SCALAR>

Size gum::credal::VarMod2BNsMap< GUM_SCALAR >::getEntrySize ( ) const

Get the number of IBayesNet stored.

Definition at line 261 of file varMod2BNsMap_tpl.h.

                                                         {
      return myHashNet_.size();
    }

References myHashNet_.

◆ getFullBNOptsFromKey()

template<typename GUM_SCALAR>

std::vector< std::vector< std::vector< std::vector< bool > > > > gum::credal::VarMod2BNsMap< GUM_SCALAR >::getFullBNOptsFromKey ( const std::vector< Size > & key )

Get optimum IBayesNet (s) with structure of the given variable, modality for min or max.

Parameters

key	The constant reference to the variable, modality, min or max.

Returns: The vector of not yet constant pointers to the nets.

Definition at line 228 of file varMod2BNsMap_tpl.h.

                                                                                      {
      if (cnet == nullptr)
        GUM_ERROR(OperationNotAllowed,
                  "No CredalNet associated to me ! Can't get FullBNOptsFromKey : " << key);
 
      if (!myVarHashs_.exists(key))
        return std::vector< std::vector< std::vector< std::vector< bool > > > >();
 
      std::list< Size >& netsHash = myVarHashs_[key];   //.at(key);
 
      std::vector< std::vector< std::vector< std::vector< bool > > > > nets;
      nets.resize(netsHash.size(), sampleDef_);
 
      std::list< Size >::iterator it = netsHash.begin();
 
      for (Size i = 0; i < netsHash.size(); i++, ++it) {
        // std::vector< std::vector< std::vector < bool > > > net(sampleDef_);
        dBN::iterator it2 = myHashNet_ /*.at(*/[*it] /*)*/.begin();
 
        for (Size j = 0; j < sampleDef_.size(); j++) {
          for (Size k = 0; k < sampleDef_[j].size(); k++) {
            for (Size l = 0; l < sampleDef_[j][k].size(); l++) {
              nets[i][j][k][l] = *it2;
              ++it2;
            }
          }
        }
      }
 
      return nets;
    }

References cnet, GUM_ERROR, myHashNet_, myVarHashs_, and sampleDef_.

◆ getSampleDef()

template<typename GUM_SCALAR>

const std::vector< std::vector< std::vector< bool > > > & gum::credal::VarMod2BNsMap< GUM_SCALAR >::getSampleDef ( )

Get the sample structure.

Returns: The constant reference to the sample structure.

Definition at line 202 of file varMod2BNsMap_tpl.h.

                                                  {
      return sampleDef_;
    }

References sampleDef_.

◆ insert() [1/2]

template<typename GUM_SCALAR>

bool gum::credal::VarMod2BNsMap< GUM_SCALAR >::insert	(	const std::vector< bool > &	bn,
		const std::vector< Size > &	key )

Insert for thread fusion.

All inserted nets are optimums and none will be deleted because a better one is being inserted.

Parameters

bn	The constant reference to the net to be inserted.
key	The constant reference to the key at which we will insert the net.

Definition at line 90 of file varMod2BNsMap_tpl.h.

                                                                           {
      currentHash_            = Size(vectHash_(bn));
      std::list< Size >& nets = myVarHashs_.getWithDefault(key, std::list< Size >());   //[ key ];
 
      for (std::list< Size >::iterator it = nets.begin(); it != nets.end(); ++it) {
        if (*it == currentHash_) return false;
      }
 
      // add it
      myHashNet_.set(currentHash_, bn);   //[currentHash_] = bn;
      // insert net hash in our key net list
      nets.push_back(currentHash_);
      // insert out key in the hash key list
      myHashVars_.getWithDefault(currentHash_,
                                 std::list< varKey >()) /*[currentHash_]*/.push_back(key);
      return true;
    }

References currentHash_, myHashNet_, myHashVars_, myVarHashs_, and vectHash_.

◆ insert() [2/2]

template<typename GUM_SCALAR>

bool gum::credal::VarMod2BNsMap< GUM_SCALAR >::insert	(	const std::vector< Size > &	key,
		const bool	isBetter )

Thread insert.

Parameters

key	The key at which the net will be inserted.
isBetter	`True` if the net is a better one, i.e. it gave better marginals.

Returns: True if the net was inserted, false otherwise.

Definition at line 110 of file varMod2BNsMap_tpl.h.

                                                                                              {
      if (isBetter) {
        // get all nets of this key (maybe entry does not exists)
        std::list< Size >& old_nets
            = myVarHashs_.getWithDefault(key, std::list< Size >());   //[ key ];
 
        // for each one
        for (std::list< Size >::iterator it = old_nets.begin(); it != old_nets.end(); ++it) {
          // get all keys associated to this net
          std::list< varKey >& netKeys
              = myHashVars_.getWithDefault(*it, std::list< varKey >());   //[ *it ];
 
          // if we are the sole user, delete the net entry
          if (netKeys.size() == 1) {
            myHashVars_.erase(*it);
          }
          // other keys use the net, delete our key from list
          else {
            for (std::list< varKey >::iterator it2 = netKeys.begin(); it2 != netKeys.end(); ++it2) {
              if (*it2 == key) {
                netKeys.erase(it2);
                break;
              }
            }
          }
        }   // end of : for each old_net
 
        // clear all old_nets
        old_nets.clear();
        // insert new net with it's hash
        myHashNet_.set(currentHash_,
                       currentSample_);   //[currentHash_] = currentSample_;
        // insert net hash in our key net list
        old_nets.push_back(currentHash_);
        // insert out key in the hash key list
        myHashVars_
            .getWithDefault(currentHash_, std::list< varKey >()) /*[currentHash_]*/
            .push_back(key);
        return true;
 
      }   // end of isBetter
      // another opt net
      else {
        // check that we didn't add it for this key
        std::list< Size >& nets = myVarHashs_.getWithDefault(key, std::list< Size >());   //[ key ];
 
        for (std::list< Size >::iterator it = nets.begin(); it != nets.end(); ++it) {
          if (*it == currentHash_) return false;
        }
 
        // add it
        myHashNet_.set(currentHash_, currentSample_);
        // insert net hash in our key net list
        nets.push_back(currentHash_);
        // insert out key in the hash key list
        myHashVars_.getWithDefault(currentHash_, std::list< varKey >()).push_back(key);
 
        /*
              // add it
              myHashNet_[currentHash_] = currentSample_;
              // insert net hash in our key net list
              nets.push_back(currentHash_);
              // insert out key in the hash key list
              myHashVars_[currentHash_].push_back(key);
        */
        return true;
      }   // end of ! isBetter
    }

References currentHash_, currentSample_, myHashNet_, myHashVars_, and myVarHashs_.

◆ setCNet()

template<typename GUM_SCALAR>

void gum::credal::VarMod2BNsMap< GUM_SCALAR >::setCNet ( const CredalNet< GUM_SCALAR > & cn )

Initialize sampleDef from the CredalNet.

Shoud only be used by InferenceEngine to initialize it's member variable.

Parameters

cn	The CredalNet to be used.

Definition at line 68 of file varMod2BNsMap_tpl.h.

                                                                               {
      auto* cpt    = &cn.credalNet_currentCpt();
      auto  nNodes = cpt->size();
      sampleDef_.resize(nNodes);
 
      for (NodeId node = 0; node < nNodes; node++) {
        auto pConfs = (*cpt)[node].size();
        sampleDef_[node].resize(pConfs);
 
        for (Size pconf = 0; pconf < pConfs; pconf++) {
          Size          nVertices = Size((*cpt)[node][pconf].size());
          unsigned long b, c;   // needed by superiorPow
          superiorPow(static_cast< unsigned long >(nVertices), b, c);
          Size nBits = Size(b);
          sampleDef_[node][pconf].resize(nBits);
        }
      }
 
      cnet = &cn;
    }

References cnet, gum::credal::CredalNet< GUM_SCALAR >::credalNet_currentCpt(), sampleDef_, and gum::superiorPow().

Referenced by VarMod2BNsMap().

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◆ setCurrentSample()

template<typename GUM_SCALAR>

void gum::credal::VarMod2BNsMap< GUM_SCALAR >::setCurrentSample ( const std::vector< std::vector< std::vector< bool > > > & sample )

Set the current thread sample and it's hash.

Parameters

sample The constant reference to the sample with structure.

Definition at line 180 of file varMod2BNsMap_tpl.h.

                                                                   {
      currentSample_.clear();
 
      for (Size i = 0; i < sample.size(); i++)
        for (Size j = 0; j < sample[j].size(); j++)
          for (Size k = 0; k < sample[i][j].size(); k++)
            currentSample_.push_back(sample[i][j][k]);
 
      // std::cout << sample << std::endl;
      // std::cout << currentSample_ << std::endl;
 
      currentHash_ = Size(vectHash_(currentSample_));
    }

References currentHash_, currentSample_, and vectHash_.

Member Data Documentation

◆ cnet

template<typename GUM_SCALAR>

const CredalNet< GUM_SCALAR >* gum::credal::VarMod2BNsMap< GUM_SCALAR >::cnet

protected

A pointer to the CredalNet to be used.

Definition at line 104 of file varMod2BNsMap.h.

Referenced by VarMod2BNsMap(), getFullBNOptsFromKey(), and setCNet().

◆ currentHash_

template<typename GUM_SCALAR>

Size gum::credal::VarMod2BNsMap< GUM_SCALAR >::currentHash_

protected

The current sampled IBayesNet hash.

Definition at line 99 of file varMod2BNsMap.h.

Referenced by insert(), insert(), and setCurrentSample().

◆ currentSample_

template<typename GUM_SCALAR>

dBN gum::credal::VarMod2BNsMap< GUM_SCALAR >::currentSample_

protected

The current sampled IBayesNet.

Definition at line 97 of file varMod2BNsMap.h.

Referenced by getCurrentSample(), insert(), and setCurrentSample().

◆ myHashNet_

template<typename GUM_SCALAR>

hashNet gum::credal::VarMod2BNsMap< GUM_SCALAR >::myHashNet_

protected

Map id - dBN : get a net from it's id.

Definition at line 82 of file varMod2BNsMap.h.

Referenced by getBNOptsFromKey(), getEntrySize(), getFullBNOptsFromKey(), insert(), and insert().

◆ myHashVars_

template<typename GUM_SCALAR>

hashVars gum::credal::VarMod2BNsMap< GUM_SCALAR >::myHashVars_

protected

Map id - list(varKey) : get all variables, modalities associated to this optimal net id.

Definition at line 89 of file varMod2BNsMap.h.

Referenced by insert(), and insert().

◆ myVarHashs_

template<typename GUM_SCALAR>

varHashs gum::credal::VarMod2BNsMap< GUM_SCALAR >::myVarHashs_

protected

Map varKey - list(id) : get all optimal nets id from the given key : variable, modality and min=0 ( or max=1 ).

Definition at line 85 of file varMod2BNsMap.h.

Referenced by getBNOptsFromKey(), getFullBNOptsFromKey(), insert(), and insert().

◆ sampleDef_

template<typename GUM_SCALAR>

std::vector< std::vector< std::vector< bool > > > gum::credal::VarMod2BNsMap< GUM_SCALAR >::sampleDef_

protected

Since all samples have the same structure, this will be used as default initialization (copy constructor) for any sample.

Definition at line 94 of file varMod2BNsMap.h.

Referenced by getFullBNOptsFromKey(), getSampleDef(), and setCNet().

◆ vectHash_

template<typename GUM_SCALAR>

std::hash< std::vector< bool > > gum::credal::VarMod2BNsMap< GUM_SCALAR >::vectHash_

protected

The hash fuction.

Requires c++11/0x.

Definition at line 101 of file varMod2BNsMap.h.

Referenced by insert(), and setCurrentSample().

The documentation for this class was generated from the following files:

agrum/CN/tools/varMod2BNsMap.h
agrum/CN/tools/varMod2BNsMap_tpl.h

Public Member Functions

Protected Attributes

Private Types

Detailed Description

Member Typedef Documentation

◆ dBN

◆ hashNet

◆ hashVars

◆ varHashs

◆ varKey

Constructor & Destructor Documentation

◆ VarMod2BNsMap() [1/2]

◆ VarMod2BNsMap() [2/2]

◆ ~VarMod2BNsMap()

Member Function Documentation

◆ getBNOptsFromKey()

◆ getCurrentSample()

◆ getEntrySize()

◆ getFullBNOptsFromKey()

◆ getSampleDef()

◆ insert() [1/2]

◆ insert() [2/2]

◆ setCNet()

◆ setCurrentSample()

Member Data Documentation

◆ cnet

◆ currentHash_

◆ currentSample_

◆ myHashNet_

◆ myHashVars_

◆ myVarHashs_

◆ sampleDef_

◆ vectHash_